Book Image

Hands-on DevOps

By : Sricharan Vadapalli
Book Image

Hands-on DevOps

By: Sricharan Vadapalli

Overview of this book

<p>DevOps strategies have really become an important factor for big data environments.</p> <p>This book initially provides an introduction to big data, DevOps, and Cloud computing along with the need for DevOps strategies in big data environments. We move on to explore the adoption of DevOps frameworks and business scenarios. We then build a big data cluster, deploy it on the cloud, and explore DevOps activities such as CI/CD and containerization. Next, we cover big data concepts such as ETL for data sources, Hadoop clusters, and their applications. Towards the end of the book, we explore ERP applications useful for migrating to DevOps frameworks and examine a few case studies for migrating big data and prediction models.</p> <p>By the end of this book, you will have mastered implementing DevOps tools and strategies for your big data clusters.</p>
Table of Contents (22 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
11
DevOps Adoption by ERP Systems
12
DevOps Periodic Table
13
Business Intelligence Trends
14
Testing Types and Levels
15
Java Platform SE 8

Big data systems life cycle


Big data systems are built in accordance with the data life cycle model, which can be broadly categorized in the following stages:

  • Data discovery
  • Data quality
  • Ingesting data into the system
  • Persisting the data in storage
  • Analytics on the data
  • Data governance
  • Visualizing the results

We will study them in detail next.

Data discovery into the system

Data discovery, like in the traditional process, ingests raw data from multiple source systems; however, the data will be divergent in volume, variety, and velocity when it comes to transforming it into business insights. Leveraging the power of big data, the data discovery process enables data wrangling and data enrichment facilitates combining datasets to recreate new perspectives and interactive visual analytics. An interactive data catalog facilitates guided search capabilities and enables us to thoroughly analyze and understand the data quality. A matured and robust data discovery process ensures possible data correlations...